With the rapid development of the wireless communication technology, people puts forward higher requirement on the quality and the comfortableness of voice communication, in which, the comfortable and natural hands free communication environment is becoming the increasing demand of people. However, the existence of echoes influences the communication quality, and may make the communication system be unable to work normally when being serious. So, an effective measure must be taken to suppress the echo and eliminate its influence, thereby improving the quality of the voice communication.
An echo canceller generally adopts a self-adaptive echo cancellation method. The self-adaptive filter generates, through identifying an impact response to an acoustic feedback channel, a signal that is same with an echo, and then subtracts the echo signal from a mixed signal of a near-end voice and the echo, to achieve the purpose of the echo cancellation. In this way, it not only can guarantee that the influence on the voice quality is minimum, but also obtains maximum suppression on the echo. The greatest characteristic of the self-adaptive echo cancellation technology is that: it does not limit space in which the acoustic feedback channel locates, that is, regardless of the internal space size, regardless of its internal furnishings, and regardless of the position in which the speaker is, it tracks the change of the acoustics characteristic in the room automatically and suppress to the maximum extent the echo and even howling caused by the acoustic feedback. Thus, it is the key for the acoustic echo cancellation to rapidly and automatically identify and track the characteristic of the acoustic feedback of the LRM system channel in a cockpit or room.
However, in the case of real communication, there are some phenomena, such as, double-talk and path mutation, and these phenomena all influence the convergence performance of the self-adaptive filter, resulting in the echo not be able to be canceled effectively. The performance merits of a path change detection module and a double-end detection module in the echo canceller directly influence the effects of the echo suppression. When a double-talk mode is detected, it is needed to control the self-adaptive filter to stop the coefficient update, otherwise, the uprush of error signals causes the self-adaptive filter to be divergent; and it is needed to restart the filter during the path mutation, so as to track rapidly the path changes and eliminate the echo better.
The traditional double-end detection module generally adopts a Geigel method and a correlation detection method. The complexity of the Geigel method is low and it is easy to be realized, but the determination of a threshold is very difficult, and the effect under the noise environment is relatively bad; while the correlation detection method mainly relies on detections of the near-end and far-end voices, which causes the performance of the filter to worsen when the noise is larger or the path is mutated.
The traditional path detection module adopts a structure of master-slave filters, and the added slave filter is generally a window with a total length of 128 ms, and is used for covering the whole echo path; however, the cost and complexity of this method are both very high. At the same time, after the path is changed, the echo changes as well, which makes the performance of the double-end detection method, of which the original performance is good, worsen due to threshold failure.